HSS4303B – Intro to EpidemiologyJan 25, 2010 – Natural History of Disease

International Culture & Development Week

• http://www.scdi-icdw.uottawa.ca/

• Today:– 2:30pm: Launch with Allan Rock, Tabaret Chapel– 4pm: “Casino capitalism”, UCU205 chaired by ME!

The Midterm

Date Pros Cons

Feb 11

Feb 25

The Midterm

Date Pros Cons

Feb 11 -get it over with-less material-more help

-only a week away!

Feb 25 -more time to study (including spring break)

-more material-Erin and I will not be available during reading week

Which will it be?!!!!

The Abstract

• Due on Thursday at midnight• Follow instructions carefully (including how to

submit it!!!)• Any issues thus far?

Poster Assignment

• I’ll be posting details soon• Seek out partners• I’ll be asking for names of teams soon• If you don’t know anyone in the class, let me

know and I’ll see what I can do

Tutorial

• Erin will be available on Thursday• I will upload more exercises tonight (or

tomorrow) for you to try before seeing her

(If you do a Google image search for “tutorial” these are the first two hits:)

Review• Mortality Rate (MR)

– #deaths/# at risk• Case Fatality Rate (CFR)

– #deaths/#diagnosed• Cause-specific mortality rate

– #deaths from specific cause / # at risk• Years of potential life lost (YPLL)

– Expected lifespan – observed lifespan• Disability assisted life year (DALY)

– (years of life lost) +(years of productive life lost)• Disability Adjusted Life Expectancy (DALES)• Proportionate Mortality Ratio (PMR)

– #deaths due to a cause / #deaths total• Quality Adjusted Life Years (QALYs)

– #years lived X quality index (0->1)

Review• Survival Rate (SR)

– (# initial subjects - # subjects dead or censored) / (#initial subjects)

• Relative Survival Rate (RSR)– SR among subjects/ SR among total population

• Cause-Specific Survival Rate (CSS)– (#initial subjects - #subjects dead from specific cause) / (#initial subjects)

Review

• Age-specific mortality rate– The mortality rate of a specific population within a

specific age stratum• Age-adjusted mortality rate

– Total mortality rate for a population, after its age distribution has been adjusted to resemble a standard (reference) population

• Crude Mortality (Death) Rate– Un-adjusted total mortality rate

Review• Standardized Mortality Ratio (SMR)

– (#observed deaths per year) / (#expected deaths per year)

• Direct Standardization– Computes age-adjusted mortality rate by multiplying the

age-specific rates from the test population by the age-specific populations from the reference

• Indirect Standardization– Computes age-adjusted mortality rate by multipling the

age-specific rates from the reference population by the age-specific populations from the test population

– SMR x (crude death rate in standard population)

Artefact• (Artifact is the American

spelling; both are acceptable)

• a spurious finding, such as one based on either a faulty choice of variables or an overextension of the computed relationship

Interpreting observed changes in mortality

• Changes in mortality– Artifactual

• Problems with the numerator• Problems with the denominator

– Real • Identify possible explanations• Develop a hypothesis

Artifactual trends in mortality

1. Numerator Errors in diagnosis

  Errors in age

  Changes in coding rules

  Changes in classification

2. Denominator Errors in counting population

  Errors in classifying by demographic characteristics (e.g., age, race, sex)

  Differences in percentages of populations at risk

Cohort

From Latin “cohors”, it was the basic unit of the Roman Legion.

Cohort

Refers to a bunch of people who move together.

Cohort

Refers to a bunch of people who move through time together.

Cohort

• A group of people who share a particular experience or characteristic(s) over a period of time– Irish women born in 1950– Engineers who smoked between the ages of 25-30– HSS students in 3rd year

Now…. An example

• Pertussis– Whooping cough– Highly contagious bacterial infection– Effective, well tolerate vaccine that lasts several

years– One of the leading causes of vaccine-preventable

deaths in the world

Pertussis

DALYs

Source: Wikipedia

Facts

• Beginning in 1990 Canada experienced a resurgence of pertussis.

• The mean annual incidence before 1990 was 3.8 cases per 100 000 population which increased to 37.2 thereafter.

• The mean annual hospitalization rates increased from 2.7 per 100 000 before 1990 to 5.2 afterward.

• The proportion of cases in 0- to 4-year-old children decreased, whereas it increased steadily in all other age groups

• Between 1990 and 1998 the median age of cases shifted from 4.4 to 7.8 years.

The Pediatric Infectious Disease Journal: January 2003 - Volume 22 - Issue 1 - pp 22-27

So What’s Happening?

• “The sudden increase in pertussis incidence in Canada can be largely attributed to a cohort effect resulting from a poorly protective pertussis vaccine used between 1985 and 1998.” –NTEZAYABO et al, 2003

• In other words, something that happened in the 80s to infants did not manifest till the 90s in older children, as the cohort moved through time

Factors Around Cohort Effect

• Smoking behaviours differ between generations

• Income differs between generations• Geopolitical circumstances (e.g. war) differ• Health system issues may differ (e.g. infant

health care)• etc

Example

• In the UK, politicians often speak of the “cohort effect” in terms of a certain generation:– Brits born between 1925 and 1945 (centred

around 1931) experienced more rapid improvements in mortality than generations born on either side (i.e., younger and older)

WHY?

Cohort effect

• Cross sectional view– Identifies peculiarities and key messages from the

data– Which age group has the highest rates of

tuberculosis

• Cohort effect– Identifies groups with the trait or disease incidence– Group is followed over time to see if the trait

develops or disease manifests

• Cross sectional view– Identifies peculiarities and key messages from the

data– Which age group has the highest rates of

tuberculosis

• Cohort view– Identifies groups with the trait or disease incidence– Group is followed over time to see if the trait

develops or disease manifests

Cohort vs Cross-Sectional View (1900)

Table 4-14. Age-specific Death Rates per 100,000 from Tuberculosis (All Forms), Males, Massachusetts, 1880-1930

  Year

Age (yr) 1880 1890 1900 1910 1920 1930

0-4 760 578 309 309 108 41

5-9 43 49 31 21 24 11

10-19 126 115 90 63 49 21

20-29 444 361 288 207 149 81

30-39 378 368 296 253 164 115

40-49 364 336 253 253 175 118

50-59 366 325 267 252 171 127

60-69 475 346 304 246 172 95

70+ 672 396 343 163 127 95

Data from Frost WH: The age selection of mortality from tuberculosis in successive decades. J Hyg 30:91-96, 1939.

Peak mortality occurred for the 30-39 years age group (Cross sectional view)

Cohort effectTable 4-15. Age-specific Death Rates per 100,000 From Tuberculosis (All Forms), Males, Massachusetts, 1880-1930

  Year  

Age (yr) 1880 1890 1900 1910 1920 1930

0-4 760 578 309 309 108 41

5-9 43 49 31 21 24 11

10-19 126 115 90 63 49 21

20-29 444 361 288 207 149 81

30-39 378 368 296 253 164 115

40-49 364 336 253 253 175 118

50-59 366 325 267 252 171 127

60-69 475 346 304 246 172 95

70+ 672 396 343 163 127 95

Follow the cohort and the peak mortality occurs for the 20-29 years old group

The History of Disease

The History of Disease

• Age of Pestilence and Famine• Age of Receding Pandemics• Age of Degenerative and Manmade Diseases

In very very very broad terms, historians consider the history of human disease to have occurred in 3 phases:

Abdel Omran, 1971….

http://www.who.int/bulletin/archives/79%282%29159.pdf

Age of Pestilence and Famine

• High mortality rates• Wide swings in mortality rates• Little population growth• Very low life expectancy

Age of Receding Pandemics

• Less frequent epidemics• Less incident infectious disease• A slow rise in degenerative disease

Age of Degenerative and Manmade Diseases

• Cancers• Obesity• Cardiovascular disease• Diseases associated with high SES and

relatively bountiful food

• Most countries are here now

Omran defined: The Epidemiologic Transition

• a human phase of development witnessed by a sudden and stark increase in population growth rates brought about by medical innovation in disease or sickness therapy and treatment, followed by a re-leveling of population growth from subsequent declines in procreation rates– Wikipedia

Cf. Demographic Transition1. stage one, pre-industrial society, death rates

and birth rates are high and roughly in balance2. stage two, that of a developing country, the

death rates drop rapidly due to improvements in food supply and sanitation, which increase life spans and reduce disease

3. stage three, birth rates fall due to access to contraception, increases in wages, urbanization, etc.

4. stage four: there are both low birth rates and low death rates. Birth rates may drop to well below replacement level as has happened in countries like Germany, Italy, and Japan

5. Stage five: sub-replacement fertility

Cf. Demographic Transition

Perfectly correlated to per capita alcohol consumption in these countries.

Epidemiologic transition from 1990 to 2020

Natural History of Disease

refers to a description of the uninterrupted progression of a disease in an individual from the moment of exposure to causal agents until recovery or death

Natural history of a disease in a patient

Natural history of a disease in a patient

Death

Survival

An idealized depiction of the natural history of disease.

Natural history of coronary heart disease.

Natural History of Disease

• …is not the same as the changing patterns of disease in a population

• E.g., the distribution of CHD over SES groups may change over time as a society changes….

• But the natural history of CHD will not change

“Pyramid” or “Iceberg” of Disease

-- SCREENING

Prognosis

• “the likely outcome of a disease”• The important endpoint in the Natural History

of Disease

“Petosiris to Nechepso”

Prognosis

• Identify the end points– Death– Survival with disability– Survival without disability– Relapse

• Delay the endpoints• Improve the quality of life• Measures of prognosis

Measures of prognosis

1. Case-fatality ratio2. Mortality rates

– Person years

3. Five-year survival rate4. Observed survival (rationale for life table)5. Life table

– Kaplan-Meier method for survival

6. Median survival time7. Relative survival rate

Measures of prognosis

1. _______________– Is defined as the number of people who die of

the disease divided by the number of people who have the disease

– Is used mostly for diseases with shorter duration or acute conditions

– Is less used for diseases with low mortality and long disease span

– Alternate measure of prognosis need to be used for diseases with longer span

CFR

Measures of prognosis

2. ______________ (person-years)– Is defined as number of deaths divided by the

person-years over which the group is observed– The unit of measure is person-years (individuals

multiplied by the number of years the individuals are observed)

– The risk for different individuals is assumed to be the same; for one person-year is equivalent to another

Mortality Rate

Measures of prognosis

3. ______________ rate• Is the percentage of patients who are alive 5

years after treatment begins or 5 years after diagnosis

• For cancer is used as a measure of treatment efficacy

• Is not effective in late diagnosis and when treatment is not effective

• Is not effective when the survival is less than five years

Five Year Survival

Next….

• Check website tomorrow (morning? Maybe?) for uploaded exercises

• Don’t forget to finish your abstracts!• Next class: Kaplan Meier survival curves!